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Glama

COTAL actions (cotal.ai)

What COTAL is

cotal_overview
Read-onlyIdempotent

Returns a structured overview of COTAL: what it is, who it is for, when to use it, how to install it, the site's API and MCP surface, pricing, and canonical links. Call this first when a user asks what cotal.ai does. Pass section to get one part only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sectionNoWhich part of the overview to return (default: all).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds value by specifying the return content (structured overview listing sections) and reiterating that it is a safe, first-call informational tool. No contradiction; it enriches the behavioral picture without repeating annotation fields verbatim.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero filler. The first sentence front-loads the core purpose and lists content areas efficiently; the second sentence gives the only usage hint needed. Every word earns its place, and the structure makes scanning easy for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple info-retrieval tool with one optional parameter and read-only annotations, the description is complete. It tells the agent what the tool returns, when to invoke it, and how to narrow the response. No output schema exists, but the description's enumeration of included sections sufficiently sets expectations. Nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% – the `section` parameter has a complete enum and a description explaining 'Which part of the overview to return (default: all)'. The description's phrase 'Pass `section` to get one part only' adds minimal meaning beyond the schema, just clarifying the usage intent. This meets the baseline 3, nothing more.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource ('Returns a structured overview of COTAL') and enumerates the exact content areas (what it is, who it's for, install, API/MCP, pricing, links). It also explicitly frames the tool's role ('Call this first when a user asks what cotal.ai does'), which unmistakably distinguishes it from the sibling tools that perform targeted actions like searching or joining a waitlist.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance ('Call this first when a user asks what cotal.ai does') and a usage tip for the optional parameter ('Pass `section` to get one part only'). However, it does not explicitly state exclusions or contrast with specific siblings, though the general-purpose framing makes the alternative clear enough from the sibling names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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